Figure 6.

Distribution of the coefficients of variation of solution parameters. The coefficient of variation StdDev(log10Ki)/Mean(log10Ki), where {Ki}i = 1...n is any kinetic parameter, was computed for every parameter across the entire ensemble of solution sets. Their distribution is shown (red line). For comparison the distribution of the coefficient of variation of a variable X is shown (green line), where X is sampled from a uniform distribution in the interval [-5,0]. The distribution of the coefficient of variation can be approximated by a Gaussian density function N(μ, σ) with μ = 2/ and σ = 0.07 (in blue): the μ value is the coefficient of variation of the uniform distribution, while σ is the standard deviation of a random set of coefficients of variation obtained by sampling the uniform distribution in the interval [-5,0] (Fig. 7). A coefficient of variation smaller than 0.33 has a probability of random occurrence ≤ 0.0002, while the 17 parameters selected using the genetic algorithm represent 6.5% of the whole (Fig. 7), that is a coefficient of variation smaller the 0.33 have a proability of occurrence of 0.065 in the solution set.

Arisi et al. BMC Neuroscience 2006 7(Suppl 1):S6   doi:10.1186/1471-2202-7-S1-S6